Researchers from the Czech Institute of Informatics, Robotics and Cybernetics, specifically from its Industrial Informatics Department (IID) Přemysl Šůcha, Vilém Heinz and Josef Grus, successfully represented the institute at 20th International workshop on Project Management and Scheduling 2026 (PMS 2026), held in Toulouse at the prestigious LAAS-CNRS.
PMS is a well-established forum for experts in project management, optimization and scheduling — fields that develop mathematical methods for planning complex operations, from manufacturing and logistics to healthcare systems.
A major highlight of this year’s event was the invited plenary lecture by Přemysl Šůcha, head of IID, who presented his talk Machine Learning in Decomposition-Based Scheduling. His presentation explored how machine learning can be used in decomposition-based methods to solve highly complex scheduling tasks faster and more efficiently.
Scheduling problems arise whenever many interconnected tasks, people or machines must be coordinated under strict constraints. In practice, this includes applications such as hospital operating room planning, nurse rostering, or production scheduling in factories. Traditional optimization methods often divide these large problems into smaller parts that can be solved separately. Přemysl Šůcha showed how machine learning can enhance this process by learning patterns in recurring subproblems and helping optimization algorithms make decisions more quickly.
Another significant success came from Vilém Heinz, who came second in the Best Student Paper Award for his contribution Constraint and Integer Programming for Resource-Constrained Project Scheduling Problem with Transfer Times (authors Heinz Vilém, Hanzálek Zdeněk, Artigues Christian, Hebrard Emmanuel).
His research addresses a practical challenge encountered in many industrial settings: how to plan projects when resources must not only be assigned to tasks, but also physically moved between them. This may involve transporting equipment, tools or materials between different workstations or locations, sometimes using additional transport resources such as vehicles. These transfer times can significantly complicate project planning.
The awarded paper presents new exact computational methods that combine constraint programming and integer programming to solve such problems more effectively. These approaches make it possible to optimize complex projects where both task execution and resource movement must be coordinated, which is relevant for advanced manufacturing, construction, and logistics systems.
A third CIIRC contribution was presented by Josef Grus, whose paper Periodic Scheduling of Grouped Time-Triggered Signals on a Single Resource focused on challenges inspired by industrial applications. The work addressed efficient scheduling of periodic communication signals in systems where precise timing is critical, such as industrial automation and embedded control systems.
